NeuroControl of movement: system identification approach for clinical benefit

Abstract

Progress in diagnosis and treatment of movement disorders after neurological diseases like stroke, cerebral palsy (CP), dystonia and at old age requires understanding of the altered capacity to adequately respond to physical obstacles in the environment. With posture and movement disorders, the control of muscles is hampered, resulting in aberrant force generation and improper impedance regulation. Understanding of this improper regulation not only requires the understanding of the role of the neural controller, but also attention for: (1) the interaction between the neural controller and the “plant”, comprising the biomechanical properties of the musculaskeletal system including the viscoelastic properties of the contractile (muscle) and non-contractile (connective) tissues: neuromechanics; and (2) the closed loop nature of neural controller and biomechanical system in which cause and effect interact and are hence difficult to separate. Properties of the neural controller and the biomechanical system need to be addressed synchronously by the combination of haptic robotics, (closed loop) system identification (SI), and neuro-mechanical modeling. In this paper, we argue that assessment of neuromechanics in response to well defined environmental conditions and tasks may provide for key parameters to understand posture and movement disorders in neurological diseases and for biomarkers to increase accuracy of prediction models for functional outcome and effects of intervention.

Short-Term Effects of Cerebellar tDCS on Standing Balance Performance in Patients with Chronic Stroke and Healthy Age-Matched Elderly

“…A decrease in CoP parameters is generally assumed to reflect an improvement in postural stability in patients with a stroke ( 47 ). There is a strong need for more sensitive and reliable measures to be able to quantify subtle changes in standing balance performance and disentangle postural control mechanisms ( 48 ). Despite several promising methods to quantify postural control, a golden standard is still lacking ( 49 , 50 ).…”

Forearm Flexor Muscles in Children with Cerebral Palsy Are Weak, Thin and Stiff

“…We subtracted the no-hand force from the with-hand forces and used a linear least-squares technique to identify the biomechanical model (Schouten et al, 2008; Meskers et al, 2015): $\begin{array}{c}left{F}_{WH}(t)-F_{NH}(t)=m{l}^2{\theta }^{″}(t)+B{\theta }^{\prime }(t)+K\theta (t)+K_1{\theta }^2(t)\\ +K_2{\theta }^3(t)+mgcos(\theta (t))\end{array}$ where F WH ( t ) and F NH ( t ) are the recorded forces in the with-hand and no-hand trials, m is the mass of the hand (point mass), l is the length of the hand from the wrist joint, θ( t ) is the recorded wrist angle and θ′( t ), θ″( t ) are its first and second derivatives (angular velocity and acceleration) computed numerically by differentiating the recorded joint angle, g is the gravitational acceleration and finally K and B are the joint stiffness and viscous parameters, respectively. The second and third-order power of joint angles (θ 2 ( t ), θ 3 ( t )) were also included in the model to account for nonlinear changes of joint biomechanics as a function of joint angle (Sobhani Tehrani et al, 2013).…”

Toward adaptive deep brain stimulation for dystonia

“…7 In line with this, a correlation has been described between the increase in GPi stimulation frequency and the development of bradykinesia. 26 The appearance of these side effects after stimulation suggests that DBS interferes with both pathological activity in the CBGTC circuits 39 and physiological activity that helps to control voluntary movements. 9,29 To improve efficacy and limit side effects, much effort has been put into developing DBS systems that only stimulate when pathological activity and clinical symptoms are present.…”

“…9,29 To improve efficacy and limit side effects, much effort has been put into developing DBS systems that only stimulate when pathological activity and clinical symptoms are present. 39 Future DBS devices might be able to deliver electrical stimulation in response to pathological oscillations by increasing electrical current on demand-that is, only when, for example, the oscillatory power exceeds a threshold. 46 This adaptive form of DBS (aDBS) has already been successfully applied in nonhuman primate models of PD 56 by using the occurrence of cortical spikes as a biomarker.…”